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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprsarchives-XL-7-W3-15-2015</article-id>
<title-group>
<article-title>Satellite-based assessment of grassland yields</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Grant</surname>
<given-names>K.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Siegmund</surname>
<given-names>R.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wagner</surname>
<given-names>M.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hartmann</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Institute for Crop Science and Plant Breeding, Bavarian State Research Center for Agriculture (LfL), Freising, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>GAF AG, Munich, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>28</day>
<month>04</month>
<year>2015</year>
</pub-date>
<volume>XL-7/W3</volume>
<fpage>15</fpage>
<lpage>18</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2015 K. Grant et al.</copyright-statement>
<copyright-year>2015</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-7-W3/15/2015/isprs-archives-XL-7-W3-15-2015.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-7-W3/15/2015/isprs-archives-XL-7-W3-15-2015.pdf</self-uri>
<abstract>
<p>Cutting date and frequency are important parameters determining grassland yields in addition to the effects of weather, soil
conditions, plant composition and fertilisation. Because accurate and area-wide data of grassland yields are currently not available,
cutting frequency can be used to estimate yields. In this project, a method to detect cutting dates via surface changes in radar images
is developed. The combination of this method with a grassland yield model will result in more reliable and regional-wide numbers of
grassland yields. For the test-phase of the monitoring project, a study area situated southeast of Munich, Germany, was chosen due to
its high density of managed grassland. For determining grassland cutting robust amplitude change detection techniques are used
evaluating radar amplitude or backscatter statistics before and after the cutting event. CosmoSkyMed and Sentinel-1A data were
analysed. All detected cuts were verified according to in-situ measurements recorded in a GIS database. Although the SAR systems
had various acquisition geometries, the amount of detected grassland cut was quite similar. Of 154 tested grassland plots, covering in
total 436 ha, 116 and 111 cuts were detected using CosmoSkyMed and Sentinel-1A radar data, respectively. Further improvement of
radar data processes as well as additional analyses with higher sample number and wider land surface coverage will follow for
optimisation of the method and for validation and generalisation of the results of this feasibility study. The automation of this
method will than allow for an area-wide and cost efficient cutting date detection service improving grassland yield models.</p>
</abstract>
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